Senior AI Engineer – Generative AI, Pharmacovigilance
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Job Description
AI Engineer building Generative AI, RAG, and Agentic AI solutions for EVERSANA’s pharmacovigilance technology team. Developing compliant drug-safety monitoring and case-processing applications.
Responsibilities:
- Design, develop, and deploy AI/ML solutions for Pharmacovigilance business processes
- Build Generative AI applications using OpenAI, Azure OpenAI, Anthropic, Llama, or equivalent LLM platforms
- Develop domain-specific AI assistants for Pharmacovigilance operations and safety case management
- Build intelligent document processing solutions for source documents, ICSRs, safety narratives, and regulatory reports
- Build and optimize RAG-based applications using vector databases
- Develop prompt engineering frameworks and evaluation methodologies
- Fine-tune domain-specific models using pharmacovigilance datasets
- Develop AI agents and workflow automation capabilities using Agentic AI frameworks
- Develop and implement evaluation strategies for LLM and Agentic AI applications
- Integrate safety systems, clinical data sources, APIs, and enterprise applications into AI workflows
- Develop data pipelines for structured and unstructured Pharmacovigilance data
- Work with structured and graph-based data sources to support advanced AI applications
- Deploy AI models and Generative AI applications into production environments
- Implement monitoring, model evaluation, drift detection, performance optimization, observability, and telemetry using OpenTelemetry
- Maintain scalable, secure, and compliant AI infrastructure
- Support CI/CD and automated deployment pipelines for AI applications
- Ensure AI solutions comply with GxP, GVP, FDA, EMA, MHRA, and internal quality standards
- Support AI validation, audit readiness, traceability, and documentation requirements
- Implement Responsible AI and model governance practices
- Partner with Pharmacovigilance SMEs and Product Managers to understand business requirements
- Translate regulatory and safety requirements into scalable AI solutions
- Support demos, proof-of-concepts, and innovation initiatives
Requirements:
- Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, Physics, Bioinformatics, or a related discipline
- 5+ years of hands-on experience in AI/ML engineering
- Experience developing and deploying production-grade AI applications
- Mandatory experience developing solutions using Agentic AI frameworks
- Experience with Generative AI, LLMs, RAG, NLP, and AI/ML application development
- Experience working with cloud platforms and production AI/ML deployment environments
- Python — mandatory
- SQL
- REST APIs
- PostgreSQL
- Machine Learning and Deep Learning
- Transformer Models
- Generative AI, LLM, and fine-tuning
- NLP
- Azure OpenAI / OpenAI APIs
- LangChain
- Agentic AI frameworks — mandatory
- crewAI
- LlamaIndex
- Prompt Engineering
- RAG Architecture
- Semantic Search
- Vector Databases
- Azure and AWS; GCP preferred
- MLflow
- Docker
- Kubernetes
- CI/CD Pipelines
- OpenTelemetry
- Understanding of Pharmacovigilance processes is preferred
- Experience with Graph Databases and GraphRAG is preferred
- Knowledge of Clinical Trial and Regulatory ecosystems is preferred
- Experience working in GxP-validated environments is preferred
- Experience implementing AI solutions within regulated Healthcare or Life Sciences environments is preferred
- Experience with AI observability, evaluation, monitoring, and model governance is preferred
Benefits:
- Certified as a Great Place to Work
- Equal Opportunity Employer
- Diversity, Equity & Inclusion commitment
- Remote work option
- Professional development and investment in employee development
- Opportunity to work on next-generation AI products and innovation initiatives
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